1. Field of the Invention
The present invention relates to an apparatus for detecting a vertex of an image and a method for the same. In more particular, the present invention relates to an apparatus for detecting the optimal vertex based on vertexes in a region of interesting (ROI) input by a user and a method for the same.
2. Description of the Related Art
Recently, technologies of modeling an object by employing an object image of a real world, which has been previously photographed, as a background image and selecting and adjusting coordinates of vertexes of the object has been spotlighted.
In general, in order to perform the modeling of the object, the user must select vertexes of the object and adjust the selected vertexes to correct coordinates. As described above, the vertex detection in the process of the object modeling has been performed through an algorithm having the interaction with many users and a slow processing rate. In addition, since the vertex detection in the process of the object modeling has never been attempted in a mobile phone, object modeling cannot be performed in situ.
When the object modeling is performed in the mobile phone, the selection of correct vertexes and fine adjustment are required due to the low degree of precision of a touch screen mounted on the mobile phone, In this case, the user must perform many interaction operations, so that the user may feel fatigue.
FIG. 1 is a flowchart for vertex detection in modeling steps according to the related art.
According to one example of the related art, Hengel has suggested a scheme of modeling a scene by inputting a video sequence for the purpose of object modeling of the real world. The object modeling scheme of Hengel is disclosed in a reference [A. v. d. Hengel, et al., “Video Trace: Rapid Interactive Scene Modeling from Video,” ACM Transactions on Graphics, vol. 26, no. 3, article 86, July, 2007.] in detail.
Referring to FIG. 1, according to the Hengel scheme, in order to select the vertexes of an object, the whole images of each frame of a video are subject to a segmentation process, and the edges of the images are detected based on superpixels. However, the mobile phone having a low computing power spends significant processing time to perform the above procedure. In addition, according to the Hengel scheme, in order to select vertexes at correct positions, a selection operation based on mouse-input and an adjustment operation must be repeatedly performed. However, the mobile phone equipped with a touch screen having the low degree of sensing precision has a difficulty in the correct selection of the vertexes and the fine adjustment.
Meanwhile, the details of edge detection based on superpixels is disclosed in a reference [X. Ren, et al., “Learning a Classification Model for Segmentation,” In Proc. 9th ICCV, vol. 1, pp. 10-17, 2003.].
According to another related art, in a modeling scheme of reconstructing a building in a real world into a 3-D structure, Gibson has suggested a scheme of overlapping a frame box model serving as a basic unit with an image without directly selecting a vertex, and repeatedly adjusting a vertex of a suggested model to a vertex of the building in the image, thereby matching the vertexes with each other. However, similarly to the Hengel scheme, the Gibson scheme has a difficulty in the fine adjustment under the environment of the mobile phone.
The Gibson modeling scheme is disclosed in a reference [S. Gibson, et al., “Interactive Reconstruction of Virtual Environments from Video Sequences,” Computers & Graphics, vol. 27, pp. 293-301, 2003] in detail.